Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems where the core input is data. Troves of raw information, are streaming in and stored in enterprise data warehouses. There is much to learn by mining it. Advanced capabilities can be built with it. Data science is ultimately about using this data in creative ways to generate business value.
All the search engines (e.g. Google) make use of data science algorithms to deliver the best result for our searched query in fraction of seconds. Considering the fact that, Google processes more than 20 petabytes of data every day. Had there been no data science, Google wouldn’t have been the ‘Google’ we know today.
The entire digital marketing spectrum runs on data science. Starting from the display banners on various websites to the digital bill boards at the airports – all of them are decided by using data science algorithms. They can be targeted based on users past behaviour. This is the reason why you see ads of one product while your friend sees ad of another product in the same place at the same time.
Data science seeks its implementation in various ways in retail sector. The companies implement different models of data analysis to enhance the customers’ shopping experiences, through visual merchandising, inventory management, new store locations etc. In this regard, all the transactions, e-mails, and search inquiries, previous purchases, etc. are analysed and processed to optimize the marketing moves and merchandising processes.
- INTRODUCTION TO DATA SCIENCE Copy
- PYTHON BASICS Copy
- COMPLEX DATA TYPES Copy
- PROGRAMMING WITH PYTHON Copy
- FUNCTIONS AND LIBRARIES Copy
- EXCEPTIONS AND ERROR HANDLING Copy
- WORKING WITH DATA – DATA FROM EXTERNAL SOURCES Copy
- DATA WRANGLING Copy
- NUMPY, PANDAS & SEABORN Copy
- GIT (BONUS LECTURE FOR ASPIRING PROGRAMMERS) Copy
DATA VISUALIZATION USING TABLEAU